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Releases: torajharsh/aether-scale

ASME v1.0.1

17 Feb 21:42
@torajharsh torajharsh
v1.0.1
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ASME v1.0.1 Latest
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ASME v1.0.1 - High-Integrity Tensor (HIT) Flow Optimization

Release v1.0.1: The "Frictionless" Breakthrough

Aether-Scale Matrix Engine (ASME) moves from foundation to high-velocity optimization with the introduction of Internal Pre-scaling.

The Day 1 Performance Leap

Immediately following the launch of V1.0.0, intensive benchmarking revealed a "Mantissa Friction" bottleneck during deep-stack operations. V1.0.1 resolves this by internalizing the Unit-Domain Flow (UDF) logic, shifting the scaling burden from the runtime loop to the initialization phase.

  • Performance Gain: ~30.7% throughput increase in GPU-bound environments.
  • Architectural Standard: Formalizing the High-Integrity Tensor (HIT) Flow.
  • Integrity: 0.00 MSE maintained (Bit-perfect parity with standard paths).

🛠 Technical Changes

  • Optimized run_sequence: Now utilizes a pre-scaled weight buffer to reduce arithmetic operations by 50% per layer.
  • JIT Stability: Refined harmonic_product for backward compatibility with TorchScript.
  • Signal Preservation: Enhanced handling for deep-stack architectures (150+ layers) to ensure deterministic outcomes at the signal horizon.

Benchmark Summary (Tesla T4)

Metric V1.0.0 (Baseline) V1.0.1 (Optimized) Delta
150-Layer Latency 3.63 ms 2.51 ms +30.7%
Numerical Drift 0.000 0.000 Absolute Parity

Developed by Raj Harsh at the ASME Foundation.

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ASME v1.0.0

17 Feb 20:48
@torajharsh torajharsh
v1.0.0
2fb8497
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ASME v1.0.0

ASME v1.0.0: The Aether-Scale Awakening

Overview

I am proud to announce the initial release of the Aether-Scale Matrix Engine (ASME). This version introduces the foundational Unit-Domain Flow (UDF) architecture, enabling deep-stack matrix operations with zero numerical drift.

Key Breakthroughs

  • Zero Mantissa Friction: Achieved bit-perfect 0.00 MSE across 100+ sequential layers.
  • Efficiency Boost: Verified 21% reduction in latency compared to traditional post-multiplication normalization stacks.
  • Computational Integrity: Adheres to the High-Integrity Tensor Standard (HITS) for deterministic, drift-free neural computation in mission-critical AI frameworks.

Technical Contents

  • Harmonic Product Kernels: Fused scaling/multiplication logic via TorchScript for maximum GPU throughput.
  • AetherEngine Core: The primary developer interface for high-precision sequence processing.
  • Integrity Suite: Standardized testing for cross-hardware mathematical validation.

Developed by Raj Harsh at the ASME Foundation.

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